Paper to be presented at the
35th DRUID Celebration Conference 2013, Barcelona, Spain, June 17-19
From Hacker to Entrepreneur:
How Openness to Experience, Creativity and
Extrinsic Motivation Impact Distinct Stages of the Entrepreneurial Proc
Maria Anna Halbinger
Copenhagen Business School
Department of Innovation and Organizational Economics
[email protected]
Abstract
Drawing on the literature on entrepreneurship and social psychology, this study proposes that dispositional, cognitive
and motivational mechanisms determine different stages of the entrepreneurial process. Using unique survey data of
659 community members, the paper conjectures that the personal trait openness to experience increases the likelihood
of becoming an entrepreneur as well as exposing oneself to opportunities ? a prerequisite for entrepreneurial opportunity
discovery. The article further suggests that creativity fosters both opportunity recognition and entrepreneurship, and that
extrinsic motivation is positively associated with diverse forms of exploitation. The empirical analyses confirm the effects
with respect to openness. But while extrinsic motivation, overall, is an indicator for opportunity commercialization, it does
not demonstrate explanatory power for firm foundation. Instead, the results show that creativity has a strong positive
effect throughout the entrepreneurial process from opportunity discovery and exploitation to transition to
entrepreneurship.
Jelcodes:O31,-
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From Hacker to Entrepreneur:
How Openness to Experience, Creativity and Extrinsic Motivation Impact Distinct Stages
of the Entrepreneurial Process
ABSTRACT
Drawing on the literature on entrepreneurship and social psychology, this study proposes that
dispositional, cognitive and motivational mechanisms determine different stages of the
entrepreneurial process. Using unique survey data of 659 community members, the paper
conjectures that the personal trait openness to experience increases the likelihood of becoming an
entrepreneur as well as exposing oneself to opportunities – a prerequisite for entrepreneurial
opportunity discovery. The article further suggests that creativity fosters both opportunity
recognition and entrepreneurship, and that extrinsic motivation is positively associated with
diverse forms of exploitation. The empirical analyses confirm the effects with respect to
openness. But while extrinsic motivation, overall, is an indicator for opportunity
commercialization, it does not demonstrate explanatory power for firm foundation. Instead, the
results show that creativity has a strong positive effect throughout the entrepreneurial process
from opportunity discovery and exploitation to transition to entrepreneurship.
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INTRODUCTION
The past decade in entrepreneurship literature has witnessed the establishment of the term
entrepreneurship as a process. In particular, the process model by Shane and Venkataraman
(2000) in which individuals discover and exploit opportunities has been widely adopted and is
considered as theoretical backbone in the field (Aldrich and Cliff 2003). However, this process
model has not been empirically analyzed from an end-to-end perspective. Hence, it remains
unclear how individuals’ differences influence the process stages opportunity exposure,
recognition and exploitation. This study aims to close this research gap by analyzing what type of
individual attributes and motivation may be associated with which stage of entrepreneurial
process. This is an important topic for several reasons. First, given the prevalence of the process
perspective in the entrepreneurship literature, researchers are interested in gaining a deeper
understanding on how individuals identify, evaluate and transform opportunities into business
ideas (Shane 2012). Second, the decision to exploit an opportunity has seldom been explicitly
empirically examined based on social psychology factors. Thus, this study addresses calls in the
literature to analyze on a more fine-grained level the dynamics behind the transition to
entrepreneurship (Shane et al 2003). Third, since entrepreneurship is not limited to firm
foundation only, research in this vein needs more studies where further exploitation modes in
markets and hierarchies are considered (Shane 2012). Consequently, pursuing this research
question involves the examination of entrepreneurship in the sense of both new firm foundation
and other forms of entrepreneurial exploitation. Finally, this study addresses venture capitalists’
and innovation managers’ strong interest in people’s entrepreneurial attributes, in particular when
it comes to the composition of founding or innovation teams. Furthermore, since organizations
are typically on the lookout for new ideas to fuel their innovation processes, managers may
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benefit from knowing more about when and why opportunities are available on the market for
exploitation purposes. The phenomenon is under-researched due to several factors. First, scholars
seem to have lacked representative data. It is difficult to collect data from individuals operating
on entrepreneurship-related opportunities, at different process stages involving different
exploitation forms. Studies that do discuss individuals’ attributes and motivation are either
conceptual (e.g. Shane et al 2003) or focus on one single stage of the entrepreneurial process,
preferably the final stage and potential incentives associated with that (e.g. Lazear 2005, Zhao
and Seibert 2006, Taylor 1996). Research in this vein disregards that people select out at earlier
stages in the process which can lead to the questionable assumption that personality, cognitive
and motivational attributes influence all stages equally (Shane et al 2003). Thus, this paper
distinctly considers three potential drivers of the specific process stages intending to help explain
why particular individuals (1) expose themselves to opportunities, (2) recognize them, (3)
become entrepreneurs or (4) chose other modes of exploitation. First, the study investigates the
influence of openness to experience, a personal trait characterizing intellectually curious
individuals (McCrae 1987). It is assumed that individuals scoring high on this trait have an
increased likelihood of both exposing themselves to opportunities and transition to
entrepreneurship. Associated results help to understand more distinctively the role of personality
traits in early versus later stages of the entrepreneurial process. Second, the study moves its
attention towards the individual’s creativity and thinking style which – based on the investment
theory of creativity (Sternberg and Lubart 1996) – determines individuals’ decision on how to use
their creative skills intending to “buy low and sell high” (Sternberg 2006, p. 87). Scholars in the
field note that entrepreneurship requires the recognition of opportunities where individuals
connect complementary pieces of information and transform them into business ideas (Baron
2006). I argue that creativity first facilitates this recombination task triggering opportunity
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recognition and second, in notion with “selling high” increases the likelihood of firm foundation.
The thinking style angle of creativity and corresponding findings are important since they have
not been deployed in previous entrepreneurship literature. Finally, I hypothesize that the decision
to exploit an opportunity arises from motivational mechanisms. Actions of extrinsically
motivated individuals are result-directed and hence, these individuals pursue particular activities
in expectation of the outcome rather than the activity itself (Deci and Ryan 1985). Hence,
extrinsic motivation is assumed to be core in entrepreneurial career intentions and to positively
influence both opportunity commercialization and firm foundation. This article examines the
influence of these mechanisms in a stepwise approach. In a series of logistic regressions, the
milestones in the entrepreneurial process from opportunity exposure, recognition, firm foundation
and opportunity commercialization function as dependent variables. The analyses are conducted
on the context of hacker- and makerspace members in the Northern, English- and Germanspeaking countries in Europe as well as United States, Canada, Australia and New Zealand since
this represents a setting where all stages and factors under investigation are present. Due to their
use-context, these specific individuals have been found to be exposed to complementary, both
need- and solution based information (e.g. von Hippel 1988), solve unsolved problems (e.g.
Jeppesen and Lakhani 2010), generate ideas with business potential (e.g. (Lilien et al 2002), and
become entrepreneurs (e.g. Shah and Tripsas 2007). The results attract attention in terms of its
ambiguous effect in the opportunity discovery stage. In line with Zhao and Seibert (2006), the
results show that openness to experience is positively associated with entrepreneurial status. But
while a high score on openness increases individuals’ likelihood to expose themselves to
opportunities, it significantly decreases the likelihood of the opportunity’s value recognition. This
finding is interesting regarding both the literature on the early stages of the entrepreneurial
process and on search on the individual level, for instance studies on invention processes (e.g.
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5
Maggitti et al 2012). Moreover, creativity appears to be an important driver of entrepreneurship
throughout all process stages. This adds a new perspective to the investment theory of creativity
(Sternberg and Lubart 1996) and allows exhibiting the role of cognitive properties as distinct
from the personality trait openness to experience. Furthermore, the analysis shows that extrinsic
motivation positively affects the exploitation of an opportunity in the form of commercialization
but it does not explain firm foundation. The discussion on the commercialization of opportunities
contributes to search-related literature, in particular research on distributed sources of innovation
since the results help to explain why opportunities and business ideas are available on the market.
The paper proceeds as follows. Based on the literature on entrepreneurship and psychology the
study outlines the theoretical framework. I derive hypotheses for how openness to experience,
creativity and extrinsic motivation influence opportunity discovery and exploitation (figure 1).
Secondly, I specify the sample and data collection process, present the econometric approach and
test the hypotheses. Finally, the article presents and discusses the results.
-----------------------------------------Insert Figure 1 about here
------------------------------------------ENTREPRENEURIAL PROCESS AND OPPORTUNITIES
In line with Shane and Venkataraman (2000), this article regards entrepreneurship as a process in
which individuals pursue opportunities based on three major stages: opportunity exposure,
recognition and exploitation. Accordingly, the first stage captures opportunity exposure which is
two-fold in the sense that the individual must a) possess prior knowledge that is b)
complementary to new information inputs. In the second stage, the individual recombines the
different information pieces thereby creating new means-ends relationships. In short, the
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individual recognizes an opportunity as such by seeing the entrepreneurial value of the
information. These first two transition stages together define the discovery of an opportunity
(figure 1). However, the two stages are also distinct. The pure existence and accordingly, the
exposure to opportunity-related information is objective. Instead, recombining the information
and recognizing the value of an opportunity is shaped in people’s minds and hence of rather
subjective nature (Shane 2012). In the final process stage, the individual exploits the recognized
opportunity through a) new firm foundation, or, b) other forms within and outside existing
organizations such as the commercialization of new products, services, patents or trademarks.
Although this article applies a process perspective to entrepreneurship, I follow the notion that
stages do not necessarily pursue a chronological order (Shane 2012). Taken together, the
entrepreneurial process represents a blueprint with individuals and opportunities at its core and
where ideal-typically the individual is the agent who passes through the process stages by
pursuing an entrepreneurial opportunity. In line with prior work, I define opportunities as
situations where people face profits referring to products, services, models or processes with a
positive price-cost relationship expectation when introduced at the market (Casson 1982, Shane
2012). Moreover, in previous studies entrepreneurial opportunities are explicitly associated with
new market performance rather than with optimization or efficiency-increasing mechanisms of
existing products, services, models or processes. Thus, both types of opportunities share the aim
to be appropriate for a given context and hence, pursue the trajectory of usefulness. However, the
entrepreneurial opportunity stands out with regards to its novelty (e.g. Kirzner 1997, Shane and
Venkataraman 2000). But due to the disequilibrium of opportunity-related information and
beliefs among people, not all opportunities that exist are identified, recognized and
entrepreneurially exploited (Schumpeter 1934, Hayek 1945, Casson 1982, Kirzner 1997, Shane
and Venkataraman 2000). By implication, only some individuals and not others are aware of
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existing opportunities, and again, only a subset recognizes the value and exploits the
opportunities for entrepreneurial purposes. Hence, entrepreneurial behavior is affected by
opportunities, but still, they do not completely define the process (Shane et al 2003). Thus, this
paper focuses on the individual-related rather than the opportunity-related angle of the
phenomenon and dedicates a distinct view on the key personal attributes in opportunity discovery
and exploitation.
Sub-phases of Opportunity Discovery: Opportunity Exposure and Opportunity Recognition
Opportunity discovery requires individuals a) to be exposed to information that is complementary
to prior knowledge and b) to successfully combine and leverage relevant information inputs
necessary to recognize the opportunity’s value. In the following, the paper discusses personal and
cognitive factors that determine the opportunity exposure and the dynamics required for their
recognition.
The role of openness to experience on opportunity exposure and entrepreneurship
Openness to experience is a dimension of the Five-Factor Model of personality and captures an
individual’s general interest for new experiences (McCrae 1994). Accordingly, individuals with
high scores on the generally stable and heritable trait exhibit patterns of intellectual curiosity and
a propensity for adventures and new challenges. Hence, the intrinsic interest for the new typically
affects various areas of the individual’s life and is not limited to one specific domain (McCrae
1994). Furthermore, the disposition influences the individual’s receptiveness to information and
experience from the surrounding world (McCrae 1994). This again, is a necessary requirement
for opportunity discovery in general, and opportunity exposure in specific. More precisely, in
order to discover an opportunity, an individual needs to get exposed to information inputs that are
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complementary to the knowledge the individual already possesses (e.g. Shane 2000). The
knowledge thereby can stem from information about user needs (von Hippel 1986), market or
technology trends, slack resources and market environmental shifts (Venkataraman 1997, Shane
and Venkataraman 2000). But this implies two aspects: first, individuals need to be equipped
with a specific stock of prior information and second, they need to get exposed to new
information. Consequently, I assume that individuals characterized by high scores on openness,
have a higher chance to face and take in new information inputs that are relevant for
opportunities. Open individuals are “programmed” to first of all seek for new situations and
second, they are open-minded to receive new inputs stemming from these situations. At the same
time, since it is argued that individuals’ prior knowledge is distinct and determined by
experiences in the past (Venkataraman 1997), open-minded individuals might also have more
different and various stocks of information compared to individuals with a more closed nature.
Hence, the more open a person is, the higher the likelihood that the individual possesses a rich
and various knowledge base. And moreover, the more open people are, the higher is additionally
the likelihood that these people seek for new situations exposing themselves to new information
inputs. Thus, this study conjectures that individuals with high scores on the disposition are more
likely to possess and get access to these two types of information and hence have a higher
likelihood to get exposed to entrepreneurial opportunities. At the same time, exploiting these
opportunities might involve the transition to entrepreneurship and hence, the formation of an
organization. Since this is most likely a new experience for an individual – or at least a new
challenge - I assume that highly open individuals might have a tendency to pursue this
occupational path. This is also in line with existing research in psychology literature suggesting
that openness to experience influences vocational interest and organizational change (McCrae
1994). Starting a new business is an adventurous undertaking and requires the entrepreneur to act
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flexible upon new situations. Thus, people scoring high on the openness to experience dimension
may feel attracted to these kinds of challenges and self-select into entrepreneurship. Open
individuals have a tendency to seek unfamiliar situations and entrepreneurship might offer these
circumstances on a regular basis. Hence, highly open-minded people might not feel deterred but
instead enjoy the new challenge of starting a business where everything is new and nothing is set.
Accordingly, it is suggested that individuals with high dispositions on openness have “an interest
in varied experience for its own sake” (McCrae 1987, p. 1259). In other words, these intellectual
curious individuals have an inherent enjoyment of making new experiences. Thus, I assume that
the transition to entrepreneurship offers this exact environment for open individuals since many
factors related to the firm foundation are adhoc unknown, challenging and most presumably new.
In the same vein, a comparative study showed that entrepreneurs score higher on openness to
experience than managers. Accordingly, entrepreneurs exhibit higher levels of innovative
problem-solving or business related concerns (Zhao and Seibert 2006). Overall, I argue that firm
foundation is a setting in which individuals can make novel experiences providing valuable cues
for those who score high in openness for experience. Moreover, high scores in openness provide
mental schemas increasing the likelihood to come across opportunities. Thus, I hypothesize:
Hypothesis 1: Openness to experience increases the likelihood of a) opportunity exposure and b)
firm foundation
The role of creativity on opportunity recognition and entrepreneurship
To discover an opportunity, exposure is required but not sufficient. People must also transform
the information they were exposed to into a “business idea” (Shane 2012, p.17). This is an
important milestone in the process since knowledge about an opportunity per se might be,
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objectively, “useless” as long as it lacks entrepreneurial context. Thus, individuals need to
undergo the subsequent mental step and make the appropriate connections in their information
stocks (Baron 2006). This involves linking hitherto unconnected, heterogeneous pieces of
knowledge that stem from the individual’s prior and newly absorbed knowledge. As an outcome
of this step, people are able to see the new means-ends relationships required for value
recognition (Shane and Venkataraman 2000, Shane 2012). However, the identification of these
relationships is difficult. Researchers argue that not all individuals are equally skilled to perform
this task (Ward et al 1997) and consider cognitive mechanisms at the core of the phenomenon
(e.g. Kaish and Gilad 1991, Busenitz and Barney 1997, Mitchell et al 2004). Thus, this study
draws on the literature on cognitive science, where it is argued that the cognitive style plays a
major role in how individuals process information and perform at specific tasks (Sternberg 1988).
Cognitive or thinking styles exhibit people’s tendency of how to make use of their skills,
commonly leveraging own strengths. Accordingly, I assume that the connection of the
complementary pieces of knowledge is based on people’s preferences to use their recombination
skills. At the same time, recombination is the core premise of creativity. Creativity has been
discussed from different perspectives in previous literature, for example as a process or its
outcome (e.g. Amabile 1983, Weisberg 1988, Amabile et al 2005), as skills or thinking styles
(e.g. Sternberg 1985). This study considers the factor from the investment theory of creativity and
attributes creativity to people’s decision about how to deploy their creative abilities (e.g.
Sternberg and Lubart 1996, Sternberg 2006) resulting in both novel and useful outcomes
(Amabile 1996, Sternberg and Lubart 1996). From this perspective, creativity is more a decision
than just possessing a creative ability. Accordingly, an individual is not only equipped with
creativity skills but decides to think in novel ways about existing information, to make new,
unconventional connections and investigates and produces new ideas (Sternberg 2006). Thus, this
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article suggests, that an individual’s preference for deploying creative skills for recombination
purposes influences whether or not the individual makes the appropriate connections between
information stocks, sees new means-ends relationships and finally recognizes the opportunity as
such. In other words, the initially objective, opportunity-related information is shaped in the
creative individual’s mind into a subjectively perceived opportunity with entrepreneurial value.
Consequently, creativity, from an investment theory point of view, is assumed to have a positive
impact on opportunity recognition. In line with the notion to “buy low and sell high” (Sternberg
2006, p. 87), creative people may not only generate creative outcomes such as ideas, or
entrepreneurial opportunities, that might be initially misjudged and perceived of low quality.
What makes them stand out as creative individuals , is “selling high” by making others perceive
the outcomes of their (creative) investment as valuable (Sternberg and Lubart 1996, Sternberg
2006). Hence, one way of “selling high” in the sense of demonstrating the opportunity’s value to
others, may be its application in an organizational setup. Firm foundation may function as viable
option for creative individuals with an opportunity at hand. Thus, I conjecture that individuals
with high scores on creativity deploy their creative skills (in the investment theory sense of the
term) and “sell an opportunity high” by becoming an entrepreneur. Since creativity is
independent of the opportunity’s origin, meaning that it can be acquired from someone else
(Amabile 1997), firm foundation is independent of whether or not the individuals themselves
recognized the opportunity as such. Thus, I hypothesize:
Hypothesis 2: Creativity increases the likelihood of a) of opportunity recognition and b) firm
foundation
The Role of Extrinsic Motivation on Opportunity Exploitation
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Although an opportunity holds out the prospect that a recombination of resources or information
might result in profit (Shane 2012) not all opportunities that have been discovered are finally
exploited. (Shane 2000, Shane 2001). Thus, this article follows the notion that the nature of the
opportunity alone cannot explain the entrepreneurial process but that the motivation behind the
decision to further pursue and exploit the opportunity is a distinctive factor in entrepreneurship
(Shane et al 2003). Hence, in order to understand what drives the exploitation of an opportunity
one needs to understand individuals’ motivation to engage in this step of the entrepreneurial
process. People’s motivation influences whether or not they start an activity, for how long they
keep on doing it and how much effort they put into it (Campbell and Pritchard 1976). Previous
entrepreneurship literature identified several pecuniary and non-pecuniary benefits that are
important motivators. For instance, individuals engage in the exploitation of an opportunity when
they expect financial rewards (e.g. Shepherd and De Tienne 2005, Dunne et al 1988, Campbell
1992, Taylor 1996) and when expected costs, time and efforts associated with the opportunity are
lower than the expected gains (Kirzner 1973, Schumpeter 1934, Venkataraman 1997). Hence, the
expectation about the opportunity’s outcome can constitute a decisive factor in the decision to
pursue the opportunity.
Research further identified non-pecuniary motivators, such as the
expectation of autonomy (e.g. Blanchflower and Oswald 1998, Taylor 1996), need for
achievement capturing a person’s tendency to take over tasks where they are highly responsible
for outcomes (e.g.McClelland 1961, Collins et al 2000) and self-efficacy exhibiting individuals’
belief that they succeed in task accomplishment (e.g. Bandura 1997, Chen et al 1998). This gives
reason to suggest that the outcome-driven perspective is at the heart of the entrepreneurial nature
and that the expectation to achieve specific goals is a core driver of entrepreneurship.
Accordingly, it is conjectured that individuals who are driven by rewards and outcomes of an
activity rather than the activity itself, are susceptible for entrepreneurial activities and engage in
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the exploitation of opportunities to achieve their goals. In social psychology research, this
concept refers to extrinsic motivation. Extrinsic motivation is concerned with the desire to exert
efforts to engage in an activity in order to achieve a goal apart from the activity itself (Deci and
Ryan 1985). Thus, I assume that extrinsically motivated individuals may engage in the
exploitation of an opportunity when they expect pecuniary or non-pecuniary benefits from this
activity. As suggested in previous research, this study does not limit exploitation to firm
foundation only (Shane 2012) and applies a broader definition of opportunity exploitation
capturing both the exploitation through the organizational setup of a new firm and further setups
in markets and hierarchies. In short, this paper distinguishes between the transition to
entrepreneurship operationalized through firm foundation and opportunity commercialization,
measured by new products, services, patents or trademarks. Overall, I conjecture that
extrinsically motivated individuals in their aim to achieve their goals are more likely to exploit
opportunities through either firm foundation or commercialization.
Hypothesis 3: Extrinsic motivation increases the likelihood of a) opportunity commercialization
and b) firm foundation
DATA AND METHOD
Data Collection and Assembling of Sample
To empirically test the forwarded hypotheses, this study draws on self-collected survey data on
659 community members in Northern, English- and German-speaking Europe, the United States,
Canada, Australia and New Zealand. The survey was conducted in a web-based format from May
to July 2012 on members of hacker- and makerspaces. Hacker- and makerspaces are operated by
communities offering registered members physical and online platforms for problem-solving,
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idea exchange and collaboration in areas such as IT-related software and hardware, material
processing and arts. In this context, a higher-level perspective on the term hacker and maker is
applied. This study considers them as community members who share the common interest to
use, develop and enhance technologies, materials, or goods beyond their original purpose and
standard usage. Before selecting a survey approach, I considered the practices and activities in a
hacker- and makerspace context and sought ex ante surveying to understand their meaning
(Brewer 2000, Barley and Kunda 2001). Thus, I gathered insider information about the
environment under investigation following the approach of previous studies in similar empirical
settings (e.g. Jeppesen and Frederiksen 2006). This enabled a comprehensive understanding of
culture, norms, language and ethics of the potential respondents. I deployed an iterative
combination of field observations, interviews and test studies supplemented by a think aloud
systematic (Forsyth and Lessler 1991), to extrapolate the appropriate research design. In this way,
the study design, questions’ content and sequences appropriate to the empirical context were
developed in a stepwise approach. The web-based format was chosen because the
communication, problem-solving activities and collaboration in hacker- and makerspaces are
mainly IT based. Moreover, all responses were anonymous and voluntary since the interviews
exhibited confidentiality to be a prevailing sensitive issue across the communities. For reliability
and validity purposes, the survey underwent off- and online testing and piloting within different
communities in Europe. Based on these insights the data was collected in three steps. In a first
preparation stage and to ensure the trustworthiness of the study within the community, the
administrator of a hacker- and makerspaces consortia announced the survey on three particular
online platforms where key members and administrators of the target sample are registered
members. Second, e-mails were sent to 392 community mailing lists and administrators with the
request to forward it to the community in the Northern, English- and German-speaking countries
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in Europe as well as United States, Canada, Australia and New Zealand. Since 23 spaces were not
active nor accessible, a reminder was sent after eight to ten working days to the remaining 369
spaces whereof 143 were from Europe, 208 from the United States and Canada and 18 from
Australia and New Zealandi. The sample of hacker- and makerspaces was selected by (1)
community status, (2) community purpose, (3) conditions of membership, and (4) accessibility of
community. In this way, the study captures hacker- and makerspaces registered as “active” on the
official hacker consortium website and exclude those with purposes other than hacking or making
such as spaces with exclusively commercial or educational intentions. Moreover, organizations
with employed staff to run the community and spaces with IT-security arrangements preventing
community-external contact or access were excluded. In order to study the phenomenon of
entrepreneurship, the analyses includes individuals spanning between 16-72 years old whereof
90.37% are between 16 and 48. Based on previous entrepreneurship studies, this span
corresponds to the age spectrum where individuals are most likely to engage in the
entrepreneurial process (Aldrich and Kim 2007, Oezcan and Reichstein 2009). The survey itself
covers various personal occupational-related facets of respondents and is composed of singleand multiple-choice questions and short free text questions. Following a logical sequence of
questions including interrelated modules, the questionnaire asks for information on the firm- and
individual-level. In this way, the dataset provides insights on demographic, dispositional,
cognitive and motivational aspects of the individual in addition to facts on firms and founding
events respectively. To meet the requirement for accurate examination of the individual’s
personality-, creativity- and motivation-related aspects (Shane et al 2003), constructs are based
on measures used in psychological studies.
Reasoning for Hacker- and Makerspaces as Appropriate Study Choice
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Entrepreneurial action is dependent on both individual characteristics and factors in the
surroundings. Studies on the macro level highlight how context effects shape the individual’s
likelihood to become an entrepreneur. From this perspective, new venture formation is influenced
for example by market and geographical conditions (e.g. Carroll and Swaminathan 2000,
Sorenson and Audia 2000), the individual’s organizational affiliation (e.g. Oezcan and Reichstein
2009) and moreover, the social environment (e.g. Aldrich and Zimmer 1986). But since firm
foundation is the result of human action rather than of environmental effects, macro level studies
were subject to criticism due to their shortcomings on the individual-level effects (e.g. Thornton
1999, Shane et al. 2003). In recent years, a stream of research emerged taking both perspectives,
at least to some extent, into consideration. This research strand analyzes hobbyists and
communities, as part of the individual’s environment, as hatchery for entrepreneurial
opportunities and argues that communities are contexts within which members generate
innovative outcomes (e.g. von Hippel 1988, Jeppesen and Frederiksen 2006). Taking both,
context and individual-related effects into consideration, this study required a setting where all
variables under investigation were present in order to test the hypotheses. At the same time,
highlighting the mechanisms of the individual’s attributes required data from subjects in
reasonably comparable situations. Taken together, this asks for a setting of a reasonably
homogeneous population and where – at least from a social context perspective - the variation
between subjects is minimized. Unless in experimental designs, meeting these requirements is a
complex task and appropriate settings in natural environments are rare, respectively. This is why
this study focuses on members of hobbyist communities, since it has been evidently shown, that
communities represent contexts within which individuals dedicate much of their time, thus
minimizing the influence of other contexts, and where members report their greatest creative
achievements in life, exemplarily in open software development (Lakhani and Wolf 2005). With
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regards to innovation activities, new information technologies have been found to leverage these
effects and become increasingly important for knowledge exchange purposes (e.g. Jeppesen and
Frederiksen 2006). Thus, this paper focuses on individuals in communities that use these
technologies as basis for interaction and assumes that most of the new information inputs that
these individuals encounter, stem from these environments. At the same time, due to the
community context, this analysis is based on individuals situated in comparable points of
departure regarding entrepreneurship-related activities and information. It shall be noted
however, that this setting may lead to a population of study subjects which may be problematic in
the sense that the variation in the population of individuals might not be reflected in a select
sample of potential respondents. A control for the area of development, the region and the
relatedness between the hacking activity and the professional occupation is thus part of the
empirical analysis. Taken together, this provides a framework for a sample where individuals are
faced with similar conditions and, to some extent, equally likely to engage in the entrepreneurial
process. User communities are thus a relevant context to draw from since they are core of
information flow mechanisms, innovative recombination and problem-solving activities as well
as diverse forms of motivation, in particular in the area of IT (e.g. von Hippel 1986, Jeppesen and
Lakhani 2010, Jeppesen and Frederikson 2006, Lakhani and Wolf 2005). Individuals in these
communities differ regarding their “mental equipment”, the capabilities they possess and the
motivation how to make use of them. Even when an opportunity is discovered, these individuals
use different modes of exploitation, if any at all (e.g. Shah and Tripsas 2007, Mollick 2012). For
instance, some users with specific knowledge about problems, needs or trends exhibit
entrepreneurial behavior because they significantly benefit personally from obtaining solutions to
these problems (e.g. von Hippel 1986, Lerner and Tirole 2001). Others engage in the search for
opportunity-related ideas in order to win a prize (e.g. Jeppesen and Lakhani 2010) or because
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they like the activity of problem-solving for its own sake (e.g. Lakhani and Wolf 2005) and
hence, remain at stages prior to firm foundation or other forms of exploitation. At the same time
opportunities developed by particularly sophisticated users are more likely to satisfy hitherto
unknown market needs, capture higher market shares and exhibit high levels of novelty and
importance (Lilien et al 2002) which again, are determining factors for entrepreneurship (e.g.
Shane 2001). Thus, hacker and maker communities represent a setting where different individual
attributes occur and where each milestone of the entrepreneurial process represents a viable
option of exit. This allows to specifically investigate the factors distinguishing between
individuals who stay until transition to entrepreneurship or other forms of exploitation and those
who drop out in earlier stages. By choosing a setting where subjects are highly likely to be
exposed to the same kinds of information and engage in comparable activities, the analysis aims
to meet the requirement to investigate a context where potential entrepreneurs pursue “reasonably
identical opportunities” (Shane et al 2003, p. 270).
Measures
Dependent variables
This section discusses the operationalization of the dependent variables reflecting the stages in
the entrepreneurial process from opportunity exposure, recognition, commercialization and
transition to entrepreneurship.
Opportunity exposure. The dependent variable is measured by a proxy capturing the two relevant
aspects of exposure: a) the individual’s prior knowledge that is complementary to b) new
information inputs (Kaish and Gilad 1991, Shane and Venkataraman 2000). More precisely, in
line with existing research I operationalize the first component, prior knowledge, through the
user’s information about needs (von Hippel 1988) or unsolved problems (Venkataraman 1997)
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and combine it with the second component, captured by a dummy variable indicating whether or
not the individual comes across new pieces of knowledge (Shane and Venkataraman 2000). In the
case that both types of knowledge are available to the individual, heterogeneous pieces of
information encounter each other. Thus, the constructed dummy variable indicates whether or not
the individual is exposed to an opportunity. I generated the variable in a stepwise approach by
merging the question “I hack because I have unmet need(s) or unsolved problem(s) I want to
solve.” with the number of hackerspace visits (online or physically) indicating that he or she
came across new need- and solution-based information from other members.
Opportunity recognition. To measure opportunity recognition, a questionnaire item on the
individual’s hacking and development history was applied. The question had been designed in the
style of a question on firms’ innovation developments in the U.K. innovation survey which is
based on the Eurostat Community Innovation Survey (CIS) of innovation (DTI 2003). In contrast
to the rather objective phenomenon of being exposed to an opportunity, this dependent variable
captures the individual’s decision about how to take action upon the exposure of opportunityrelated information pieces. At the same time, the combination of resources and knowledge stocks
incorporates the prerequisite that the individual must have recognized a new means-endsrelationship. Thus, opportunity recognition is rather subjective and hence, distinct to the pure
existence of an opportunity (Shane 2012) and exposure, respectively. Based on this argument, I
measured if the individual had performed this combination task and generated a development
based on his hacking activities. More precisely, with reference to the CIS survey question I
generated a dummy variable for whether or not the community member had made a significantly
new development or significantly improved implementation regarding a new technology, new
combination of existing technology, or utilization of other knowledge, material or information.
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From this perspective, the information about developments based on novel combinations of
heterogeneous knowledge pieces were used as proxy for whether or not an opportunity has been
recognized.
Commercialization. In line with prior work, this study applies a less restrictive definition of
entrepreneurship where exploitation includes both firm foundation and further exploitation modes
in markets or hierarchies (e.g. Shane 2012). For a refined analysis of the determinants, the
different forms of exploitation are measured separately in the form of commercialization and firm
foundation. Hence, to construct commercialization I created a dummy variable based on survey
items asking for the number of new products, services, patents or trademarks that have been
realized to exploit the individuals’ developments.
Firm foundation. To construct firm foundation and herewith, the transition to entrepreneurship I
generated a dummy variable whether or not the individual had founded or cofounded a company
over the course of his or her lifetime.
Independent variables
The independent variables are based on measurement items developed and used in psychology
research. Unless otherwise indicated, they have been used in the original scale version. The tables
1-3 summarize survey questions, means and standard deviations. Overall, three separate principal
component factor analyses were conducted involving Kaiser criterion (Kaiser 1960) and varimax
rotation for the survey items related to personality dimensions, creativity and motivation. An
overview of rotated and unrotated factor loadings, eigenvalues, variances and scale reliability
coefficient are additionally summarized in the tables 1-3. Since the dataset involved categorical
variables, an alternative factor analysis was additionally conducted. For this purpose I performed
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21
a polychoric correlation matrix and an exploratory factor analysis where the matrix rather than
raw variables function as input. This alternative technique delivered similar but weaker results
thereby providing additional support for the results achieved in the principal component factor
analyses.
-----------------------------------------Insert Table 1-3 about here
------------------------------------------Openness to experience. Following the example of previous management-related studies (e.g.
Grant and Berry 2012), this variable was constructed by items from a scale by Donnellan et al
(2006), a consistent and validated short form of the Five-Factor Model of personality. The survey
questions are partly reverse-coded and based on a Likert scale from 1 (“strongly disagree”) to 5
(“strongly agree”). The openness to experience items are listed in table 1 a and loaded into one
factor explaining 16% of the total variance after rotation ( =0.57) (table 1 b)).
Creativity. In prior research, creativity on the individual-level has been defined and measured in
multiple ways across experiments and field studies and rated in various formats involving peers,
experts or supervisors (e.g. Amabile 1979, Shalley and Perry-Smith 2001, Grant and Berry 2011).
As depicted in table 2a), I operationalize creativity by using an adapted short version of a four
item scale developed by Sternberg (1985). The self-reported measure is based on a seven point
Likert scale from “stronlgy disagree” being 1 to “strongly agree” being 7. I chose specifically this
self-reported measure due to the underlying theoretical viewpoint on creativity highlighted above.
The study considers creativity from the perspective of the individual’s decision of how to deploy
creative skills available to him or her (Sternberg 2006). Hence, the analysis investigates a
psychological process that runs within the individual’s mind rather than between individuals or
the environment. Since this mental process is not always reflected in the individual’s behavior
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and hence not necessarily obvious to others, an external rating on creativity in this context would
be questionable. Thus, the individual him- or herself is most likely to be the only person able to
perform the rating. The creativity items loaded into one factor accounting for 51% of the total
variance after rotation ( =0.68) (table 2 b)).
Extrinsic motivation. This article applies three extrinsic motivation questions based on items from
social psychology (Deci and Ryan 1985, Gagné and Deci 2005, Ryan and Connell 1989). In line
with a study investigating a similar empirical setting, the item “I want to enhance my career
opportunities” captures an extrinsic item for other-approval (Roberts et al. 2006). The second
item “I would like to discover a business opportunity” has been adapted from the original scale
from Ryan and Connell (1989) indicating the personal importance of the goal. Finally, the third
item “the hacker community gives support to found a company” measures the extent to which an
individual is motivated to undergo an activity (in this case hacking in a community) as a mean to
obtain a specific goal (founding a company). After rotation, the motivation items yielded one
factor explaining 33% of the total variance ( =0.73) (table 3b)).
Control variables
I control for intrinsic motivation because the construct may relate to both creativity (e.g.
Amabile 1979, Csikszentmihalyi 1996, Grant and Berry 2011) and extrinsic motivation (e.g.
Amabile 1997, Deci and Ryan 1985, Gagné and Deci 2005). In line with studies related to social
psychology research, the items “I enjoy the activity of hacking itself” and “I enjoy being part of a
community” functioned as proxies for intrinsic motivation (Deci and Ryan 1985, Ryan and
Connell 1989). Both items have been adapted for this context inspired by both previous studies in
Open Software development (e.g. Lakhani and Wolf 2005) and the insights gathered while
familiarizing with the empirical context. The third item “I forget everything around me when I
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get into the Zone” refers to “flow”, a state highly associated with intrinsic motivation where
individuals, in particular in this context, enjoy an activity to the point that they lose sense of time
due to a perfect match of skills and task (Csikszentmihalyi 1996, Lakhani and Wolf 2005) (table
3 a) and b)). With regards to personality traits I controlled for agreeableness and
conscientiousness since they have been referred to entrepreneurship in prior literature (e.g. Zhao
and Seibert 2006, Shane et al 2003). Table 1a) and b) summarize the questions and further results
with regards to the principal component factor analysis conducted to obtain the constructs.
Following previous entrepreneurship studies, I controlled for demographic variables including
mean-centered age and its square term for non-linear influence (e.g. Dunn and Holtz-Eakin 2000)
and gender. Moreover, the binary variables partner and children have been used as demographic
controls since both, being in a partnership as well as having children affects the likelihood of
entrepreneurial engagement (e.g. Dunn and Holtz-Eakin 2000, Sørensen 2007, Oezcan and
Reichstein 2009). Furthermore, to see whether or not the respondent is an active member in the
community I control for contribution as a dummy variable. In addition, it is controlled for
whether the person’s hacking activity is related to his or her occupational choice and for whether
or not the person enjoys his or her occupation. By including these variables, the analysis takes
into account a) whether or not the individual’s profession, for instance entrepreneurship, is
related to the hacking activity and b) whether the enjoyment of the profession matters with
respect to the hazard of opportunity exposure, recognition, commercialization and
entrepreneurship. Additionally, the study employs a categorical variable capturing the area of
opportunity. Finally, a control for hackerspace region has been added since geographical location
has been related to entrepreneurship (e.g. Sorenson and Audia 2000).
Model descriptions
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The objective of this study is to investigate how different individual characteristics are associated
with the transition to different stages of the entrepreneurial process. The analysis operates with
four dummy dependent variables which relate to different entrepreneurship related activities.
These are opportunity exposure, opportunity recognition, commercialization and firm foundation.
The last dummy dependent variable is an indicator whether the individual established an own
firm. The different stages of the entrepreneurship process are considered to be distinct. They are
part of a common process. Yet each stage is independent of the other stages and distinct.
Individuals engaging in one stage may not necessarily engage in the others. The stages are hence
considered unrelated and modeled separately. Accordingly, this study conducts a series of logistic
regressions where the respective dependent variable represents the transition stage in the
entrepreneurial process. This allows to distinctly analyze the influence of individual attributes on
the likelihood of opportunity exposure, recognition, commercialization and the likelihood of
becoming an entrepreneur. The regressions were corrected for potential bias in standard errors
caused by heteroscedasticity by using the Huber-White sandwich estimation method. Moreover,
to test for the appropriate fit of the models, I test all regressions for potential additional
explanatory variables (linktest) and hence countervail any misspecification of the models.
Additionally, a goodness-of-fit test based on Hosmer and Lemeshow (2000) is run to assess the
match of predicted and observed frequency. The test results indicated a well specification of the
models. Finally, I test for multicollinearity, analyze the variance inflation factor and supplement
with an assessment of the correlation matrix of the respective regression analysis. Table 4 and 5
summarize descriptive statistics and the correlation coefficients for the dependent, explanatory
and control variables
RESULTS
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Table 5 exhibits the results of five logistic regressions. It presents the effects in a staged approach
following the entrepreneurial process model. This allows an analysis of the variables’ influence
on the respective process stage. The dependent variables in model 1 to 3 represent the stages
opportunity exposure, recognition and commercialization. Model 4 exhibits the effects of the
control variables on firm foundation (log likelihood -323.12345). Adding the independent
variables openness to experience, creativity and extrinsic motivation in a herewith less restrictive
Model 5 increased the explanatory power compared to Model 4. A log likelihood ratio test
exhibited a statistically significant improvement in the model fit (log likelihood -313.20982) with
a p-value for a chi-squared of 19.83 with 3 degrees of freedom. Overall, the results support
hypothesis 1a, that openness to experience increases opportunity exposure. The estimate in model
1 is significant and positive. The effect also holds in model 5 providing evidence that openness to
experience positively influences firm foundation (hypothesis 1b). Model 1 additionally exhibits
further influencing factors on opportunity exposure. The analysis demonstrates positive and
significant effects of intrinsic motivation and agreeableness, revealing that the enjoyment of the
hacking activity itself and an individual’s predisposition for cooperation and interpersonal
relationships increases the likelihood of opportunity exposure. The logistic regression models 2
and 5 strongly confirm the hypotheses 2a and b, asserting creativity as determinant factor for
opportunity recognition and firm foundation. Both age and contribution, indicating that the
individual is actively involved in the hacking community, show positive effects in model 2.
Moreover, the variable relatedness to hacking is positively influencing the likelihood to recognize
an opportunity which points out the importance of whether or not the individual’s occupation is
related to the hacking activity. Model 2 exhibits further interesting determinants of opportunity
recognition. Females are less likely to recognize opportunities as well as people scoring high on
openness to experience. Both variables show negative significant effects. As predicted in
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26
hypothesis 3a, individuals scoring high on extrinsic motivation are more likely to exploit an
opportunity for commercial purposes. However, the analysis does not support hypothesis 3b
indicating that these individuals do not necessarily exploit opportunities in the form of firm
foundation. The models 3 and 5 show that exploitation overall, is more likely in case the
individual’s occupation is related to hacking. Commercialization is also more likely if the
individual is susceptible to conscientiousness, a personal trait indicating someone’s perseverance
and hard-working attitude. Additionally, model 3 shows that creativity increases the likelihood of
commercialization exhibiting the impact of the factor on other modes of exploitation in
hierarchies and markets. Finally, age exhibits a non-linear relationship with regards to firm
foundation in model 5 and the relatedness of occupation and hacking increases the likelihood of
becoming an entrepreneur and commercialization.
-----------------------------------------Insert Table 4 and 5 about here
------------------------------------------DISCUSSION
This paper discusses reasons why there are fewer entrepreneurs than opportunities based on the
dynamics of dispositional, cognitive and motivational mechanisms along the entrepreneurial
process. In particular, it is examined which personal attributes and motivation influence which
stage in the entrepreneurial process including opportunity exposure, recognition, and exploitation
in the form of firm foundation and other forms. The study herewith addresses recent calls to
advance research on the entrepreneurial process by conducting a hitherto absent empirical
analysis of the seminal process model by Shane and Venkataraman (2000) from an end-to-end
perspective. This is done by drawing on a unique dataset on individuals from hacker and maker
communities in Northern, English- and German-speaking Europe as well as in the United States,
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Canada, Australia and New Zealand. Three mechanisms are introduced. First, the analysis shows
that individuals with high scores on openness to experience, one dimension of the Five-Factor
Model of personality capturing an individual’s open and aware nature (McCrae 1987), are more
likely to expose themselves to opportunities and to exploit them through firm foundation. Indeed,
psychologists have confirmed the positive association between openness to experience and being
an entrepreneur (e.g. Zhao and Seibert 2006). However, this study takes a step forward and shows
that this disposition particularly affects the initiation of the entrepreneurial process by
significantly influencing the opportunity exposure stage. In contrast, people scoring high on
openness are less likely to recognize opportunities in the following step. One explanation could
be that people with this disposition are constantly on the outlook for new inputs. This might come
at the expense of focusing on the subsequent task, to make the “right” connections between the
new inputs and prior knowledge. From this perspective, the information is not transformed into
business ideas and the recognition stage not accomplished. This assumption would be in line with
previous research showing that a focus of mental efforts, filtering, categorizing and selection of
relevant information are necessary steps in the process of opportunity recognition and invention
(e.g. Baron 2006, Maggitti 2012). Second, the results confirm the positive impact of creativity on
entrepreneurial activity herewith consistent with research investigating aspects of cognitive
science and pattern recognition in entrepreneurial and invention processes (e.g. Amabile 1997,
Baron 2006, Maggitti et al 2012). By applying the investment theory of creativity (Sternberg and
Lubart 1991), I find that individuals who intentionally deploy their skills for creative purposes
connect complementary pieces of knowledge required to see new-means-end relationships and
recognize opportunities. Moreover, the results show that these individuals do not stop at this
stage but are more likely to exploit the recognized opportunities via firm foundation or other
commercial purposes. Apparently, once individuals have made the decision to invest their skills,
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time and efforts to transform information pieces into business ideas, they also want a “payback”.
Based on the principle “buy low and sell high” (Sternberg 2006, p.87), they implement the
recognized opportunity in the form of firm creation or other exploitation forms such as new
products, patents or trademarks. The results add a new perspective to the investment theory of
creativity by documenting the importance of creativity in both recognizing entrepreneurial
opportunities and implementing them. Third, the results show that extrinsically motivated
individuals are more likely to exploit their recognized opportunities through commercialization
forms other than firm foundation. Since actions of extrinsically motivated people are driven by
expected outcomes, I assume that these individuals prefer exploitation forms that deliver quick
and effortless returns over firm foundation. Accordingly, they are interested in commercializing
their ideas through selling, patenting or licensing to already existing organizations. This is
interesting in two ways: First, it would explain why there are more opportunities than
entrepreneurs. Second, the results add a new perspective on the literature on search and
distributed sources of innovation: Studies in this vein argue that companies increasingly aim to
innovate by boundary-spanning search for innovation inputs stemming from distributed sources
of innovation due to their positive impact on innovation processes (e.g. Katila and Ahuja 2002,
Laursen and Salter 2006). This study’s results complement this research stream by providing
insights on the distribution of potential sources of innovation and on the underlying mechanisms
with respect to the availability of opportunities in the market. In case no existing organization can
be found to exploit the opportunity, particularly sophisticated users become entrepreneurs by
accident (Shah and Tripsas 2007). The ideas of these individuals however, represent interesting
potential sources of innovation and are thus of high economic interest for organizations due to
their significantly higher innovation degrees and success rates in the market (Lilien et al 2002).
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FIGURE 1
Conceptual Model and Hypotheses
TABLE 1a)
Personality traits: Descriptives and Factor Loadings
Unrotated factor loadings
Survey question: "Please indicate the
extent to which you agree or disagree
with each of the following statements"
Openness to experience - Items
I am not interested in abstract ideas.
I have difficulty understanding abstract
ideas.
I do not have a good imagination.
Agreeableness - Items
I sympathize with others' feelings.
I am not interested in other people's
problems.
I feel others' emotions.
I am not really interested in others.
Conscientiousness - Items
I get chores done right away.
I often forget to put things back in their
proper place.
I like order.
I make a mess of things.
Rotated factor loadings
Openness
Openness
Agree- Conscien- UniqueAgree- Conscien- Uniqueto exto exableness tiousness
ness
ableness tiousness
ness
perience
perience
Mean
STD
4.22
0 .85
0.75
0.35
-0.01
0.31
0.83
-
-
0.31
4.11
0.88
0.69
0.35
0.04
0.41
0.76
-
-
0.41
4.18
0.99
0.52
0.21
-0.08
0.67
0.57
-
-
0.67
3.95
0.88
-0.35
0.78
-0.04
0.27
-
0.86
-
0.27
3.79
-0.10
0.69
-0.05
0.51
-
0.68
-
0.51
3.53
3.99
0.89
1.01
0.91
-0.28
-0.09
0.75
0.77
-0.04
0.07
0.36
0.40
-
0.80
0.75
-
0.36
0.40
2.54
1.00
-0.20
0.08
0.60
0.59
-
-
0.6008
0.59
2.92
1.22
0.08
0.00
0.79
0.38
-
-
0.7868
0.38
3.47
3.18
1.00
1.09
-0.14
0.20
-0.09
0.07
0.60
0.73
0.61
0.42
-
-
0.5984
0.7347
0.61
0.42
TABLE 1b)
Personality traits: Eigenvalues, Variance and Cronbach’s Alpha
PLEASE DO NOT CIRCULATE
35
Unrotated
Variable
Openness
Agreeableness
Conscientiousness
Rotated
Eigenvalue
Poportion
Variance
Proportion
1.64
2.54
1.90
0.15
0.23
0.17
1.75
2.43
1.90
0.16
0.22
0.17
Cronbach's alpha
Average interitem Scale reliability
covariance
coefficient
0.25
0.57
0.40
0.78
0.34
0.63
TABLE 2a)
Creativity: Descriptives and Factor Loadings
Survey question:
"I am someone who..."
Mean
makes connections & distinctions between ideas & things
is able to grasp abstract ideas & focus my attention on
those ideas
is able to put old information, theories, & so forth together
in a new way
uses the materials around me & makes something unique
out of them
STD
Unrotated factor loadings
Factor
Uniqueness
Creativity
0.71
0.50
Rotated factor loadings
Factor
Uniqueness
Creativity
0.71
0.50
5.98
0.99
5.97
1.08
0.75
0.44
0.75
0.44
5.76
1.07
0.77
0.40
0.78
0.40
5.75
1.15
0.63
0.61
0.63
0.61
TABLE 2b)
Creativity: Eigenvalues, Variance and Cronbach’s Alpha
Unrotated
Variable
Creativity
Rotated
Eigenvalue
Poportion
Variance
Proportion
2.06
0.51
2.06
0.51
Cronbach's alpha
Average interitem Scale reliability
covariance
coefficient
0 .40
0.68
TABLE 2a)
Motivation: Descriptives and Factor Loadings
Survey question:
"I hack because..."
Extrinsic Motivation - Items
I would like to discover a business opportunity
I want to enhance my career opportunities
the hacker community gives support to found a
company
Intrinisc Motivation - Items
I enjoy the activity of hacking itself
I enjoy being part of a community
I forget everything around me when I get into the
Zone
Unrotated factor loadings
Rotated factor loadings
Factor
Factor
Factor
Factor
Extrinsic
Intrinsic Uniqueness Extrinsic
Intrinsic Uniqueness
Motivation Motivation
Motivation Motivation
Mean
STD
4.18
4.84
1.87
1.57
0.82
0.78
-0.24
-0.23
0.27
0.34
0.85
0.81
-
0.27
0.34
4.11
1.61
0.75
-0.11
0.43
0.75
-
0.43
6.31
6.00
0 .86
1.01
0.25
0.33
0.74
0.49
0.38
0.65
-
0.79
0.56
0.38
0.65
5.47
1.44
0.18
0.58
0.63
-
0.61
0.63
PLEASE DO NOT CIRCULATE
36
TABLE 3b)
Motivation: Eigenvalues, Variance and Cronbach’s Alpha
Unrotated
Variable
Rotated
Eigenvalue
Poportion
Variance
Proportion
2.04
1.25
0.34
0.21
1.98
1.32
0.33
0.22
Extrinsic motivation
Intrinsic motivation
Cronbach's alpha
Average interitem Scale reliability
covariance
coefficient
1.35
0.73
0 .17
0.32
TABLE 4
Descriptive Statistics and Correlation Coefficients (N=518)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
11
12
13
14
15
16
17
18
19
20
Variables
Exposure
Recognition
Commercialization
Firm foundation
Openness to experience
Creativity
Extrinsic Motivation
Intrinsic Motivation
Agreeableness
Conscientiousness
Mean centered age
(Mean centered age)2
Area of opportunity
Region
Occupation enjoyment
Relatedness occupationhacking
Female
Married/relationship
Children
Contribution to
community
Mean centered age
(Mean centered age)2
Area of opportunity
Region
Occupation enjoyment
Relatedness occupationhacking
Female
Married/relationship
Children
Contribution to
community
Mean
0.82
0.55
0.24
0.43
1.36e-09
4.49e-09
1.45e-09
3.06e-10
-8.22e-10
-1.99e-10
-0.38
99.94
3.55
1.64
0.63
STD
0.38
0.50
0.42
0.50
1
1
1
1
1
1
10.00
168.02
2.25
0.66
0.48
1
2
3
4
5
6
7
8
9
0.17
0.06
-0.01
0.16
0.17
0.04
0.15
0.11
-0.05
0.04
0.00
0.00
0.07
0.00
0.50
0.18
0.04
0.20
-0.03
0.13
0.00
0.05
0.11
0.05
0.02
0.06
0.02
0.18
0.01
0.13
0.13
0.04
-0.05
0.09
0.07
0.06
0.02
0.03
0.06
0.18
0.24
0.07
0.04
0.00
0.00
0.25
0.06
0.09
0.14
0.10
0.39
-0.07
0.17
0.00
0.00
0.12
-0.04
-0.04
0.09
0.00
0.16
0.26
0.16
0.05
0.16
0.00
0.09
0.32
0.06
0.00
0.07
0.06
-0.01
0.03
0.04
0.15
0.05
0.13
-0.03
0.00
0.00
-0.12
0.12
0.12
0.00
-0.12
-0.11
0.06
0.04
0.09
0.41
0.49
0.07
0.12
0.17
0.12
0.06
0.09
0.11
0.10
0.01
0.09
0.48
0.19
0.29
0.50
0.40
0.03
0.03
0.05
-0.08
0.05
0.03
0.02
0.03
0.00
0.01
0.12
0.11
-0.03
0.07
0.06
0.08
0.06
0.10
0.03
-0.06
-0.01
-0.01
0.03
0.02
0.08
-0.04
-0.08
0.94
0.24
0.10
0.15
0.06
0.02
0.06
0.11
0.018
0.20
0.01
10
0.01
-0.01
0.04
0.02
0.02
11
12
13
14
15
16
17
18
19
20
0.56
0.07
0.20
-0.02
-0.02
0.01
-0.02
0.18
-0.01
0.07
-0.00
-0.10
-0.09
-0.11
0.00
0.43
-0.01
-0.02
-0.05
-0.01
0.32
0.52
0.02
0.09
0.30
0.12
0.12
0.05
0.05
0.03
0.11
-0.08
0.05
-0.01
-0.08
0.01
-0.06
0.00
-0.11
0.39
-0.06
-0.03
0.00
-0.00
0.10
-0.01
0.06
-0.06
-0.02
TABLE 5
0.06
PLEASE DO NOT CIRCULATE
37
Determinants of Opportunity Exposure, Recognition, Commercialization and Firm
Foundation
Variables
Openness to experience
Creativity
Extrinsic Motivation
Intrinsic Motivation
Agreeableness
Conscientiousness
Mean centered age
(Mean centered age)2
Area of opportunity
Region
Occupation enjoyment
Relatedness occupation-hacking
Female
Married/relationship
Children
Contribution to community
Constant
Number of observations
Model 1
Exposure
Model 2
Recognition
0.30*
(2.33)
0.14
(1.01)
0.09
(0.68)
0.23*
(1.98)
0.26*
(2.26)
-0.13
(-1.02)
0.00
(0.23)
0.00
(0.03)
0.00
(0.05)
0.09
(0.47)
-0.320
(-1.11)
0.40
(1.42)
0.24
(0.52)
-0.01
(-0.04)
0.25
(0.61)
0.40
(0.98)
1.13*
(2.05)
-0.18+
(-1.79)
0.43***
(3.78)
-0.15
(-1.46)
0.17+
(1.72)
-0.04
(-0.39)
0.11
(1.13)
0.03*
(2.29)
0.00
(0.19)
0.03
(0.76)
-0.09
(-0.59)
-0.244
(-1.11)
0.60**
(2.79)
-0.67*
(-2.10)
0.13
(0.60)
-0.44
(-1.49)
1.20**
(2.73)
-0.88+
(-1.71)
-0.12
(-1.00)
0.30*
(2.31)
0.24*
(2.04)
0.03
(0.24)
-0.17
(-1.54)
0.19+
(1.87)
0.02
(1.23)
0.00
(0.45)
0.04
(0.72)
-0.15
(-0.83)
-0.0576
(-0.22)
0.85***
(3.48)
0.23
(0.64)
0.10
(0.40)
-0.31
(-0.94)
0.73
(1.33)
-2.22***
(-3.64)
0.05
(0.48)
0.01
(0.11)
-0.01
(-0.08)
0.08***
(4.99)
0.00*
(-2.14)
0.07
(1.61)
0.20
(1.33)
0.212
(0.95)
0.62**
(2.81)
0.14
(0.42)
0.11
(0.54)
-0.26
(-0.89)
0.19
(0.47)
-1.32**
(-2.71)
0.20+
(1.69)
0.35**
(2.66)
0.11
(1.04)
-0.06
(-0.52)
-0.03
(-0.34)
-0.04
(-0.43)
0.07***
(4.43)
0.00+
(-1.75)
0.07
(1.50)
0.06
(0.35)
0.272
(1.18)
0.51*
(2.28)
0.08
(0.25)
0.14
(0.68)
-0.28
(-0.97)
0.09
(0.22)
-1.02*
(-2.00)
518
518
518
518
518
47.21
0.00
0.08
39.21
0.00
0.07
50.90
0.00
0.09
58.64
0.00
0.11
Wald chi2
34.70
Prob > chi2
0.00
Pseudo R2
0.07
+ p<0.1, * p<0.05, ** p<0.01, *** p<0.001
i
Model 3
Model 4
Commercialization Firm foundation
Model 5
Firm foundation
The distribution of responses in the sample is composed as follows: 43.13% from Europe, 41.21% from United
States and Canada , 8.63% from Australia and New Zealand and 7.03% did not indicate their location and were thus
excluded from the analysis.